The capability to monitor the environment for chemical agents and explosives is of great importance in the current world climate. Providing large-scale coverage of public areas that could be targets to terrorist attacks would be greatly facilitated by an “always-on” distributable sensor, with the ability to differentiate between different compounds (i.e., avoiding false positives for the substance of interest). Numerous research efforts are under way to develop this type of sensor capability; however, numerous problems remain to be solved in terms of implementation.
One of the more versatile methods of chemical detection is that of optical spectroscopy. Rather than electronic or colorimetric chemical sensing techniques, which possess inherent issues with specificity and false positive rates, optical characterization presents the possibility of an unambiguous identification of the analyte of interest. The size requirements for a practically deployable optical sensor limit the total sensor size and thus the size of its components. Accordingly, the implementation of autonomous, small scale chemical and biological sensors is a growing need.
By providing an accurate sensor that can be autonomously deployed and networked, a warfighter's exposure to hazardous substances is greatly reduced. One method for identification of various chemical compounds is through vibrational spectroscopic techniques. Currently however, instruments using such techniques require human operation and are large in size compared to micro electrical mechanical sensors (MEMS). Other devices that are designed to be small and autonomous have numerous false positive readings.
Additionally, current sensors that perform Raman analysis to detect hazardous substances require curve fitting, which must be post-processed. A different approach, described in a paper by Russin et al. entitled “Harmonic Analysis with a MEMS-based Raman Spectrometer”, IEEE Sensors 2011, uses fast fourier transforms (FFTs) to accurately compare the measured spectrum with known spectra in real-time. This approach uses an absolute sum-difference calculation performed on the FFT of a time-periodic optical (in this case, Raman) signal that is obtained from a MEMS sensor. The result of the sum-difference calculation is used in a threshold determination of the presence of an analyte of interest. While useful, such approach requires precise calibration such that repeatable Raman spectra peak position can occur.
Accordingly, there is a need for a window calibration method to enable repeatable and precise harmonic analysis of optical spectra.